3D object coordinates and object instance probabilities are learned using a Decision Forest in [1]}.
The 6D pose estimation is then formulated as an energy optimization problem which compares synthetic images rendered with the estimated pose with observed depth values.
3D object coordinates are also used in [2]}, [3]}.
However, those approaches tend to be very computationally intensive due to generation and verification of hypotheses [2]}.
